Abstract: This paper describes the application of a model predictive controller to the problem of batch reactor temperature control. Although a great deal of work has been done to improve reactor throughput using batch sequence control, the control of the actual reactor temperature remains a difficult problem for many operators of these processes. Temperature control is important as many chemical reactions are sensitive to temperature for formation of desired products. This controller consist of two part (1) a nonlinear control method GLC (Global Linearizing Control) to create a linear model of system and (2) a Model predictive controller used to obtain optimal input control sequence. The temperature of reactor is tuned to track a predetermined temperature trajectory that applied to the batch reactor. To do so two input signals, electrical powers and the flow of coolant in the coil are used. Simulation results show that the proposed controller has a remarkable performance for tracking reference trajectory while at the same time it is robust against noise imposed to system output.
Abstract: This paper deals with dynamic load balancing using PVM. In distributed environment Load Balancing and Heterogeneity are very critical issues and needed to drill down in order to achieve the optimal results and efficiency. Various techniques are being used in order to distribute the load dynamically among different nodes and to deal with heterogeneity. These techniques are using different approaches where Process Migration is basic concept with different optimal flavors. But Process Migration is not an easy job, it impose lot of burden and processing effort in order to track each process in nodes. We will propose a dynamic load balancing technique in which application will intelligently balance the load among different nodes, resulting in efficient use of system and have no overheads of process migration. It would also provide a simple solution to problem of load balancing in heterogeneous environment.
Abstract: The results show that the bridge equipped with seismic isolation bearing system shows a high amount of energy dissipation. The purpose of the present study is to analyze the overall performance of continuous curved highway viaducts with different bearing supports, with an emphasis on the effectiveness of seismic isolation based on lead rubber bearing and hedge reaction force bearing system consisted of friction sliding bearing and rubber bearing. The bridge seismic performance has been evaluated on six different cases with six bearing models. The effects of the different arrangement of bearing on the deck superstructure displacements, the seismic damage at the bottom of the piers, movement track at the pier-s top and the total and strain energies absorbed by the structure are evaluated. In conclusion, the results provide sufficient evidence of the effectiveness on the use of seismic isolation on steel curved highway bridges.
Abstract: Optical 1x12 fused-taper-twisted polymer optical fiber (POF) couplers has been fabricated by a perform technique. Characterization of the coupler which proposed to be used in passive night vision application to tracking a blind sport area was reported. During the development process of fused-taper-twisted POF couplers was carried out, red LED fully utilized to be injected into the couplers to test the quality of fabricated couplers. Some characterization parameters, such as optical output power, POFs attenuation characteristics and power losses on the network were observed. The maximum output power efficiency of the coupler is about 40%, but it can be improved gradually through experience and practice.
Abstract: One of the methods for detecting the target position
error in the laser tracking systems is using Four Quadrant (4Q)
detectors. If the coordinates of the target center is yielded through the
usual relations of the detector outputs, the results will be nonlinear,
dependent on the shape, target size and its position on the detector
screen. In this paper we have designed an algorithm with using
neural network that coordinates of the target center in laser tracking
systems is calculated by using detector outputs obtained from visual
modeling. With this method, the results except from the part related
to the detector intrinsic limitation, are linear and dependent from the
shape and target size.
Abstract: This paper shows the potential system benefits of
simple tracking solar system using a stepper motor and light sensor.
This method is increasing power collection efficiency by developing
a device that tracks the sun to keep the panel at a right angle to its
rays. A solar tracking system is designed, implemented and
experimentally tested. The design details and the experimental results
are shown.
Abstract: Shadows add great amount of realism to a scene and
many algorithms exists to generate shadows. Recently, Shadow
volumes (SVs) have made great achievements to place a valuable
position in the gaming industries. Looking at this, we concentrate on
simple but valuable initial partial steps for further optimization in SV
generation, i.e.; model simplification and silhouette edge detection
and tracking. Shadow volumes (SVs) usually takes time in generating
boundary silhouettes of the object and if the object is complex then
the generation of edges become much harder and slower in process.
The challenge gets stiffer when real time shadow generation and
rendering is demanded. We investigated a way to use the real time
silhouette edge detection method, which takes the advantage of
spatial and temporal coherence, and exploit the level-of-details
(LOD) technique for reducing silhouette edges of the model to use
the simplified version of the model for shadow generation speeding
up the running time. These steps highly reduce the execution time of
shadow volume generations in real-time and are easily flexible to any
of the recently proposed SV techniques. Our main focus is to exploit
the LOD and silhouette edge detection technique, adopting them to
further enhance the shadow volume generations for real time
rendering.
Abstract: Opinion extraction about products from customer
reviews is becoming an interesting area of research. Customer
reviews about products are nowadays available from blogs and
review sites. Also tools are being developed for extraction of opinion
from these reviews to help the user as well merchants to track the
most suitable choice of product. Therefore efficient method and
techniques are needed to extract opinions from review and blogs. As
reviews of products mostly contains discussion about the features,
functions and services, therefore, efficient techniques are required to
extract user comments about the desired features, functions and
services. In this paper we have proposed a novel idea to find features
of product from user review in an efficient way. Our focus in this
paper is to get the features and opinion-oriented words about
products from text through auxiliary verbs (AV) {is, was, are, were,
has, have, had}. From the results of our experiments we found that
82% of features and 85% of opinion-oriented sentences include AVs.
Thus these AVs are good indicators of features and opinion
orientation in customer reviews.
Abstract: Breast skin-line estimation and breast segmentation is an important pre-process in mammogram image processing and computer-aided diagnosis of breast cancer. Limiting the area to be processed into a specific target region in an image would increase the accuracy and efficiency of processing algorithms. In this paper we are presenting a new algorithm for estimating skin-line and breast segmentation using fast marching algorithm. Fast marching is a partial-differential equation based numerical technique to track evolution of interfaces. We have introduced some modifications to the traditional fast marching method, specifically to improve the accuracy of skin-line estimation and breast tissue segmentation. Proposed modifications ensure that the evolving front stops near the desired boundary. We have evaluated the performance of the algorithm by using 100 mammogram images taken from mini-MIAS database. The results obtained from the experimental evaluation indicate that this algorithm explains 98.6% of the ground truth breast region and accuracy of the segmentation is 99.1%. Also this algorithm is capable of partially-extracting nipple when it is available in the profile.
Abstract: In this paper the use of sequential machines for recognizing actions taken by the objects detected by a general tracking algorithm is proposed. The system may deal with the uncertainty inherent in medium-level vision data. For this purpose, fuzzification of input data is performed. Besides, this transformation allows to manage data independently of the tracking application selected and enables adding characteristics of the analyzed scenario. The representation of actions by means of an automaton and the generation of the input symbols for finite automaton depending on the object and action compared are described. The output of the comparison process between an object and an action is a numerical value that represents the membership of the object to the action. This value is computed depending on how similar the object and the action are. The work concludes with the application of the proposed technique to identify the behavior of vehicles in road traffic scenes.
Abstract: This paper proposes an effective adaptation learning
algorithm based on artificial neural networks for speed control of an
induction motor assumed to operate in a high-performance drives
environment. The structure scheme consists of a neural network
controller and an algorithm for changing the NN weights in order that
the motor speed can accurately track of the reference command. This
paper also makes uses a very realistic and practical scheme to
estimate and adaptively learn the noise content in the speed load
torque characteristic of the motor. The availability of the proposed
controller is verified by through a laboratory implementation and
under computation simulations with Matlab-software. The process is
also tested for the tracking property using different types of reference
signals. The performance and robustness of the proposed control
scheme have evaluated under a variety of operating conditions of the
induction motor drives. The obtained results demonstrate the
effectiveness of the proposed control scheme system performances,
both in steady state error in speed and dynamic conditions, was found
to be excellent and those is not overshoot.
Abstract: Computerized lip reading has been one of the most
actively researched areas of computer vision in recent past because
of its crime fighting potential and invariance to acoustic environment.
However, several factors like fast speech, bad pronunciation,
poor illumination, movement of face, moustaches and beards make
lip reading difficult. In present work, we propose a solution for
automatic lip contour tracking and recognizing letters of English
language spoken by speakers using the information available from
lip movements. Level set method is used for tracking lip contour
using a contour velocity model and a feature vector of lip movements
is then obtained. Character recognition is performed using modified
k nearest neighbor algorithm which assigns more weight to nearer
neighbors. The proposed system has been found to have accuracy
of 73.3% for character recognition with speaker lip movements as
the only input and without using any speech recognition system in
parallel. The approach used in this work is found to significantly
solve the purpose of lip reading when size of database is small.
Abstract: Avalanche release of snow has been modeled in the present studies. Snow is assumed to be represented by semi-solid and the governing equations have been studied from the concept of continuum approach. The dynamical equations have been solved for two different zones [starting zone and track zone] by using appropriate initial and boundary conditions. Effect of density (ρ), Eddy viscosity (η), Slope angle (θ), Slab depth (R) on the flow parameters have been observed in the present studies. Numerical methods have been employed for computing the non linear differential equations. One of the most interesting and fundamental innovation in the present studies is getting initial condition for the computation of velocity by numerical approach. This information of the velocity has obtained through the concept of fracture mechanics applicable to snow. The results on the flow parameters have found to be in qualitative agreement with the published results.
Abstract: Real-time hand tracking is a challenging task in many
computer vision applications such as gesture recognition. This paper
proposes a robust method for hand tracking in a complex environment
using Mean-shift analysis and Kalman filter in conjunction with 3D
depth map. The depth information solve the overlapping problem
between hands and face, which is obtained by passive stereo measuring
based on cross correlation and the known calibration data of
the cameras. Mean-shift analysis uses the gradient of Bhattacharyya
coefficient as a similarity function to derive the candidate of the hand
that is most similar to a given hand target model. And then, Kalman
filter is used to estimate the position of the hand target. The results
of hand tracking, tested on various video sequences, are robust to
changes in shape as well as partial occlusion.
Abstract: Existing ground movement surveillance technologies
at airports are subjected to limitations due to shadowing effects or
multiple reflections. Therefore, there is a strong demand for a new
sensing technology, which will be cost effective and will provide
detection of non-cooperative targets under any weather conditions.
This paper aims to present a new intelligent system, developed
within the framework of the EC-funded ISMAEL project, which is
based on a new magnetic sensing technology and provides detection,
tracking and automatic classification of targets moving on the airport
surface. The system is currently being installed at two European
airports. Initial experimental results under real airport traffic
demonstrate the great potential of the proposed system.
Abstract: Gaussian mixture background model is widely used in
moving target detection of the image sequences. However, traditional
Gaussian mixture background model usually considers the time
continuity of the pixels, and establishes background through statistical
distribution of pixels without taking into account the pixels- spatial
similarity, which will cause noise, imperfection and other problems.
This paper proposes a new Gaussian mixture modeling approach,
which combines the color and gradient of the spatial information, and
integrates the spatial information of the pixel sequences to establish
Gaussian mixture background. The experimental results show that the
movement background can be extracted accurately and efficiently, and
the algorithm is more robust, and can work in real time in tracking
applications.
Abstract: This paper reports on a receding horizon filtering for
mobile robot systems with cross-correlated sensor noises and
uncertainties. Also, the effect of uncertain parameters in the state of
the tracking error model performance is considered. A distributed
fusion receding horizon filter is proposed. The distributed fusion
filtering algorithm represents the optimal linear combination of the
local filters under the minimum mean square error criterion. The
derivation of the error cross-covariances between the local receding
horizon filters is the key of this paper. Simulation results of the
tracking mobile robot-s motion demonstrate high accuracy and
computational efficiency of the distributed fusion receding horizon
filter.
Abstract: It is important to give input information without other device in AR system. One solution is using hand for augmented reality application. Many researchers have proposed different solutions for hand interface in augmented reality. Analyze Histogram and connecting factor is can be example for that. Various Direction searching is one of robust way to recognition hand but it takes too much calculating time. And background should be distinguished with skin color. This paper proposes a hand tracking method to control the 3D object in augmented reality using depth device and skin color. Also in this work discussed relationship between several markers, which is based on relationship between camera and marker. One marker used for displaying virtual object and three markers for detecting hand gesture and manipulating the virtual object.
Abstract: In this article a bibliography research takes place to
track down and introduce the barriers and opportunities for the
adoption of e-Governance services mainly from the side of citizen,
that is to say, the demand side. Although governments invest
continuously in producing of e-Governance services, citizens face
difficulties to adopt these services. Barriers derive and prevent them
from using e-Governance services. Barrier is anything preventing
citizens from the adoption of e-Governance services. Barriers impede
or do not allow the adoption of e-Governance services by the
citizens. If the barriers are pinpointed, it will be possible to take them
into consideration while designing e-Governance services which the
citizens are likely to use, if the obstacles are raised. The barriers will
thus be converted in opportunities that will facilitate the adoption.
Abstract: To simulate expected climate change, we implemented a two-factor (temperature and soil moisture) field design in a forest in Ontario, Canada. To manipulate moisture input, we erected rain-exclusion structures. Under each structure, plots were watered with one of three treatments and thermally controlled with three heat treatments to simulate changes in air temperature and rainfall based on the climate model (GCM) predictions for the study area. Environmental conditions (including untreated controls) were monitored tracking air temperature, soil temperature, soil moisture, and photosynthetically active radiation. We measured rainfall and relative humidity at the site outside the rain-exclusion structures. Analyses of environmental conditions demonstrates that the temperature manipulation was most effective at maintaining target temperature during the early part of the growing season, but it was more difficult to keep the warmest treatment at 5º C above ambient by late summer. Target moisture regimes were generally achieved however incoming solar radiation was slightly attenuated by the structures.